A Survey of cuckoo search algorithm: optimizer and new applications

Cuckoo search (CS) is an efficient swarm intelligence-based algorithm that has come a long way since its start in 2009. Due to its simplicity and effectiveness, CS provides several advantages in tackling highly nonlinear optimization problems in engineering work applications. We offer an overview of the latest enhancements to this method in the past 5 years, explore the theoretical underpinning and potential research areas for future advances, and introduce novel metaheuristics to optimize computations based on explicit boosting tasks. Early studies reveal that the algorithm is viable and can exceed existing methods in performance. The CS algorithm is further validated for solving numerous technological optimization challenges. The proposed search technique is compared with the existing standard optimization algorithms. The current CS computations are merged with Lévy flight and it was the first time used to solve nonlinear benchmark challenges.